Mailman 3 October 2022 - Python-announce-list

PyCon Tanzania 2022 - Call for Speakers, Presentations, Hackathons and Workshops - 1st Reminder
by Noah . 04 Nov '22

04 Nov '22

Dear Python Community, We hope that you are all well to that end and that you have been busy working on various awesome Python Code Bases. It's almost that time of the year and we would like to engage the community for the Fourth ever Python Conference which is planned to take place from* 4th - 7th December 2022** in the beautiful and magnificent Island of ZANZIBAR.* *PyCon Tanzania*, is seeking keynote speakers and instructors to contribute to the Python Conference Program! *We are looking for speakers who would:* - Offer a Keynote speaker on an appropriate technical topic; - Offer a Technical Tutorial or Hackathon on an appropriate Python topic; *Topics must be relevant to the Python Language and Open Source Software:* - Python in Education - Python in Statistical Research - Python in Scientific Research - Python Machine Learning - Python & Artificial Intelligence - Open Source Software - Python & Cyber Security - Python Gaming Development - Cloud Computing & Virtualisation - Ideas on improving diversity and inclusiveness - Python Functional programming etc - Python and IoT *SUBMIT YOUR PRESENTATION / WORKSHOP/ HACKATHON / TUTORIAL BEFORE 05th Nov 2022 **To*: *speak(a)pycon.or.tz <speak(a)pycon.or.tz> * Regards, PyCon Tanzania 2022 Program Committee http://www.pycon.or.tz/

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Austin -- CPython frame stack sampler v3.4 is now available
by Gabriele Tornetta 30 Oct '22

30 Oct '22

I am delighted to announce the 3.4 release of Austin. If you haven't heard of Austin before, it is an open-source frame stack sampler for CPython, distributed under the GPLv3 license. It can be used to obtain statistical profiling data out of a running Python application without a single line of instrumentation. This means that you can start profiling a Python application straight away, even while it's running in a production environment, with minimal impact on performance. https://github.com/P403n1x87/austin The Austin VS Code extension provides a smooth interactive profiling experience, with interactive flame graphs straight into the text editor to allow you to quickly jump to the source code with a simple click. You can find the extension on the Visual Studio Marketplace and install it directly from VS Code: https://marketplace.visualstudio.com/items?itemName=p403n1x87.austin-vscode To see how to make the best of Austin with VS Code to find and fix performance issues, check out this blog post, which shows you the editor extension in action on a real Python project: https://p403n1x87.github.io/how-to-bust-python-performance-issues.html This latest release builds on top of the significant performance improvements introduced in the 3.3 release. Benchmarking figures (see https://github.com/P403n1x87/austin/pull/126#issuecomment-1279765640 for some of the numbers) show that Austin 3.4 continues to provide a high sample rate at low sampling intervals, with improvements of about 4x compared to Austin 3.2. One major feature of this new release is support for Python 3.11. Profiles of applications run with this version of the interpreter will have fully qualified scope names, which makes for more granular profiling data. Besides the new support for Python 3.11, the other major feature of this new release is the new MOJO binary output format that builds on top of the just-mentioned performance improvements to generate much more compact sample output files. The VS Code extension provides support for the new format starting from version 0.11.0 and so it has you covered already! More details about the MOJO file format can be found on the Wiki: https://github.com/P403n1x87/austin/wiki/The-MOJO-File-Format Other utilities to convert between file formats can be found in the austin-python Python package https://github.com/P403n1x87/austin-python More details about what's new and bugfixes can be found in the changelog https://github.com/P403n1x87/austin/blob/master/ChangeLog Austin is a pure C application that has no dependencies other than the C standard library. Its source code is hosted on GitHub at https://github.com/P403n1x87/austin The README contains installation and usage details, as well as some examples of Austin in action. Details on how to contribute to Austin's development can be found at the bottom of the page. Austin can be installed easily on the following platforms and from the following sources: Linux: - Snap Store - AUR - Conda Forge macOS: - Homebrew - Conda Forge Windows: - Chocolatey - Scoop An Austin docker image, based on the latest Ubuntu image, is also available from Docker Hub: https://hub.docker.com/r/p403n1x87/austin Austin is also simple to compile from sources as it only depends on the standard C library, if you don't have access to the above-listed sources. You can stay up-to-date with the project's development by following Austin on Twitter (https://twitter.com/AustinSampler). Austin is a free and open-source project. A lot of effort goes into its development to ensure the best performance and that it stays up-to-date with the latest Python releases. If you find it useful, consider sponsoring this project on GitHub at https://github.com/sponsors/P403n1x87. All the best, Gabriele <phoenix1987 (at) gmail.com> <p><a href="https://github.com/P403n1x87/austin">Austin 3.4</a> - frame stack sampler for CPython. (30-Oct-22)</p>

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ANN: NumExpr 2.8.4 Release
by Robert McLeod 25 Oct '22

25 Oct '22

======================== Announcing NumExpr 2.8.4 ======================== Hi everyone, This is a maintenance and bug-fix release for NumExpr. In particular, now we have added Python 3.11 support. Project documentation is available at: http://numexpr.readthedocs.io/ Changes from 2.8.3 to 2.8.4 --------------------------- * Support for Python 3.11 has been added. * Thanks to Tobias Hangleiter for an improved accuracy complex `expm1` function. While it is 25 % slower, it is significantly more accurate for the real component over a range of values and matches NumPy outputs much more closely. * Thanks to Kirill Kouzoubov for a range of fixes to constants parsing that was resulting in duplicated constants of the same value. * Thanks to Mark Harfouche for noticing that we no longer need `numpy` version checks. `packaging` is no longer a requirement as a result. What's Numexpr? --------------- Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. It has multi-threaded capabilities, as well as support for Intel's MKL (Math Kernel Library), which allows an extremely fast evaluation of transcendental functions (sin, cos, tan, exp, log...) while squeezing the last drop of performance out of your multi-core processors. Look here for a some benchmarks of numexpr using MKL: https://github.com/pydata/numexpr/wiki/NumexprMKL Its only dependency is NumPy (MKL is optional), so it works well as an easy-to-deploy, easy-to-use, computational engine for projects that don't want to adopt other solutions requiring more heavy dependencies. Where I can find Numexpr? ------------------------- The project is hosted at GitHub in: https://github.com/pydata/numexpr You can get the packages from PyPI as well (but not for RC releases): http://pypi.python.org/pypi/numexpr Documentation is hosted at: http://numexpr.readthedocs.io/en/latest/ Share your experience --------------------- Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy data! -- Robert McLeod robbmcleod(a)gmail.com robert.mcleod(a)hitachi-hightech.com

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Wing Python IDE version 9 released
by Wingware 25 Oct '22

25 Oct '22

Hi, We've just released Wing 9, which adds support for Python 3.11, reduces debugger overhead in Python 3.7+, streamlines configuration of light and dark theming, adds two light display themes, and makes improvements to auto-invocation, multi-threaded debugging, code analysis, & more. Details: https://wingware.com/news/2022-10-24 Downloads: https://wingware.com/downloads == About Wing == Wing is a full-featured but light-weight Python IDE designed specifically for Python, with powerful editing, code inspection, testing, and debugging capabilities. Wing's deep code analysis provides auto-completion, auto-editing, code navigation, early error detection, and refactoring that speed up development. Its top notch debugger works with any Python code, locally or on a remote host, container, or cluster. Wing also supports test-driven development, version control, Python package management, UI color and layout customization, and includes extensive documentation and support. Wing is available in three product levels: Wing Pro is the full-featured Python IDE for professional developers, Wing Personal is a free Python IDE for students and hobbyists (omits some features), and Wing 101 is a very simplified free Python IDE for beginners (omits many features). Learn more at https://wingware.com/

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pytest 7.2.0 released
by Ronny Pfannschmidt 25 Oct '22

25 Oct '22

pytest-7.2.0 ============== The pytest team is proud to announce the 7.2.0 release! This release contains new features, improvements, and bug fixes, the full list of changes is available in the changelog: https://docs.pytest.org/en/stable/changelog.html For complete documentation, please visit: https://docs.pytest.org/en/stable/ As usual, you can upgrade from PyPI via: pip install -U pytest Thanks to all of the contributors to this release: * Aaron Berdy * Adam Turner * Albert Villanova del Moral * Alice Purcell * Anthony Sottile * Anton Yakutovich * Babak Keyvani * Brandon Chinn * Bruno Oliveira * Chanvin Xiao * Cheuk Ting Ho * Chris Wheeler * EmptyRabbit * Ezio Melotti * Florian Best * Florian Bruhin * Fredrik Berndtsson * Gabriel Landau * Gergely Kalmár * Hugo van Kemenade * James Gerity * John Litborn * Jon Parise * Kevin C * Kian Eliasi * MatthewFlamm * Miro Hrončok * Nate Meyvis * Neil Girdhar * Nhieuvu1802 * Nipunn Koorapati * Ofek Lev * Paul Müller * Paul Reece * Pax * Pete Baughman * Peyman Salehi * Philipp A * Ran Benita * Robert O'Shea * Ronny Pfannschmidt * Rowin * Ruth Comer * Samuel Colvin * Samuel Gaist * Sandro Tosi * Shantanu * Simon K * Stephen Rosen * Sviatoslav Sydorenko * Tatiana Ovary * Thierry Moisan * Thomas Grainger * Tim Hoffmann * Tobias Diez * Tony Narlock * Vivaan Verma * Wolfremium * Zac Hatfield-Dodds * Zach OBrien * aizpurua23a * gresm * holesch * itxasos23 * johnkangw * skhomuti * sommersoft * wodny * zx.qiu Happy testing, The pytest Development Team

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Python 3.12.0 alpha 1 released.
by Thomas Wouters 24 Oct '22

24 Oct '22

As Pablo released Python 3.11.0 final earlier today, now it's my turn to release Python 3.12.0 alpha 1. *This is an early developer preview of Python 3.12* Major new features of the 3.12 series, compared to 3.11 Python 3.12 is still in development. This release, 3.12.0a1 is the first of seven planned alpha releases. Alpha releases are intended to make it easier to test the current state of new features and bug fixes and to test the release process. During the alpha phase, features may be added up until the start of the beta phase (2023-05-08) and, if necessary, may be modified or deleted up until the release candidate phase (2023-07-31). Please keep in mind that this is a preview release and its use is *not *recommended for production environments. Many new features for Python 3.12 are still being planned and written. Among the new major new features and changes so far: - The deprecated `wstr` and `wstr_length` members of the C implementation of unicode objects were removed, per PEP 623 <https://peps.python.org/pep-0623/>. - In the `unittest` module, a number of long deprecated methods and classes were removed. (They had been deprecated since Python 3.1 or 3.2). - The deprecated `smtpd` module has been removed. - A number of other old, broken and deprecated functions, classes and methods have been removed. - (Hey, **fellow core developer,** if a feature you find important is missing from this list, let Thomas know <thomas(a)python.org>.) The next pre-release of Python 3.12 will be 3.12.0a2, currently scheduled for 2022-11-14. More resources - Online Documentation <https://docs.python.org/3.12> - PEP 693 <https://www.python.org/dev/peps/pep-0693/>, the 3.12 Release Schedule - Report bugs at https://github.com/python/cpython/issues. - Help fund Python and its community at https://www.python.org/psf/donations/. And now for something completely different This is Not the Poem that I Had Hoped to Write <https://twitter.com/brian_bilston/status/1579378460610662401> This is not the poem that I had hoped to write when I sat at my desk and the page was white. You see, there were other words that I’d had in mind, yet this is what I leave behind. I thought it was a poem to eradicate war; one of such power, it would heal all the sores of a world torn apart by conflict and schism. But it isn’t. Lovers, I’d imagined, would quote from it daily, Mothers would sing it to soothe crying babies. And whole generations would be given new hope. Nope. I had grand aspirations. Believe me, I tried. Humanity examined with lessons applied. But the right words escaped me; so often they do. Have these in lieu. Brian Bilston <https://twitter.com/brian_bilston> Enjoy the new releases Thanks to all of the many volunteers who help make Python Development and these releases possible! Please consider supporting our efforts by volunteering yourself or through organization contributions to the Python Software Foundation. Regards from dusky California, Your release team, Thomas Wouters @Yhg1s Ned Deily @nad Steve Dower @steve.dower -- Thomas Wouters <thomas(a)python.org>

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[RELEASE] Python 3.11 final (3.11.0) is available
by Pablo Galindo Salgado 24 Oct '22

24 Oct '22

Python 3.11 is finally released. In the CPython release team, we have put a lot of effort into making 3.11 the best version of Python possible. Better tracebacks, faster Python, exception groups and except*, typing improvements and much more. Get it here: https://www.python.org/downloads/release/python-3110/ ## This is the stable release of Python 3.11.0 Python 3.11.0 is the newest major release of the Python programming language, and it contains many new features and optimizations. # Major new features of the 3.11 series, compared to 3.10 Some of the new major new features and changes in Python 3.11 are: ## General changes * [PEP 657](https://www.python.org/dev/peps/pep-0657/) -- Include Fine-Grained Error Locations in Tracebacks * [PEP 654](https://www.python.org/dev/peps/pep-0654/) -- Exception Groups and `except*` * [PEP 680](https://www.python.org/dev/peps/pep-0680/) -- tomllib: Support for Parsing TOML in the Standard Library * [gh-90908](https://github.com/python/cpython/issues/90908) -- Introduce task groups to asyncio * [gh-34627](https://github.com/python/cpython/issues/34627/) -- Atomic grouping (`(?>...)`) and possessive quantifiers (`*+, ++, ?+, {m,n}+`) are now supported in regular expressions. * The [Faster CPython Project](https://github.com/faster-cpython/) is already yielding some exciting results. Python 3.11 is up to 10-60% faster than Python 3.10. On average, we measured a 1.22x speedup on the standard benchmark suite. See [Faster CPython]( https://docs.python.org/3.11/whatsnew/3.11.html#faster-cpython) for details. ## Typing and typing language changes * [PEP 673](https://www.python.org/dev/peps/pep-0673/) -- Self Type * [PEP 646](https://www.python.org/dev/peps/pep-0646/) -- Variadic Generics * [PEP 675](https://www.python.org/dev/peps/pep-0675/) -- Arbitrary Literal String Type * [PEP 655](https://www.python.org/dev/peps/pep-0655/) -- Marking individual TypedDict items as required or potentially-missing * [PEP 681](https://www.python.org/dev/peps/pep-0681/) -- Data Class Transforms # More resources * [Online Documentation](https://docs.python.org/3.11/) * [PEP 664](https://www.python.org/dev/peps/pep-0664/), 3.11 Release Schedule * Report bugs at [ https://github.com/python/cpython/issues](https://github.com/python/cpython… . * [Help fund Python and its community](/psf/donations/). # And now for something completely different When a spherical non-rotating body of a critical radius collapses under its own gravitation under general relativity, theory suggests it will collapse to a single point. This is not the case with a rotating black hole (a Kerr black hole). With a fluid rotating body, its distribution of mass is not spherical (it shows an equatorial bulge), and it has angular momentum. Since a point cannot support rotation or angular momentum in classical physics (general relativity being a classical theory), the minimal shape of the singularity that can support these properties is instead a ring with zero thickness but non-zero radius, and this is referred to as a ringularity or Kerr singularity. This kind of singularity has the following peculiar property. The spacetime allows a geodesic curve (describing the movement of observers and photons in spacetime) to pass through the center of this ring singularity. The region beyond permits closed time-like curves. Since the trajectory of observers and particles in general relativity are described by time-like curves, it is possible for observers in this region to return to their past. This interior solution is not likely to be physical and is considered a purely mathematical artefact. There are some other interesting free-fall trajectories. For example, there is a point in the axis of symmetry that has the property that if an observer is below this point, the pull from the singularity will force the observer to pass through the middle of the ring singularity to the region with closed time-like curves and it will experience repulsive gravity that will push it back to the original region, but then it will experience the pull from the singularity again and will repeat this process forever. This is, of course, only if the extreme gravity doesn’t destroy the observer first. # We hope you enjoy the new releases! Thanks to all of the many volunteers who help make Python Development and these releases possible! Please consider supporting our efforts by volunteering yourself or through organization contributions to the Python Software Foundation. https://www.python.org/psf/ If you have any questions, please reach out to me or another member of the release team :) Your friendly release team, Ned Deily @nad https://discuss.python.org/u/nad Steve Dower @steve.dower https://discuss.python.org/u/steve.dower Pablo Galindo Salgado @pablogsal https://discuss.python.org/u/pablogsal

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ANN: SciPy 1.9.3
by Tyler Reddy 19 Oct '22

19 Oct '22

Hi all, On behalf of the SciPy development team, I'm pleased to announce the release of SciPy 1.9.3, which is a bug fix release. Sources and binary wheels can be found at: https://pypi.org/project/scipy/ and at: https://github.com/scipy/scipy/releases/tag/v1.9.3 ===================== SciPy 1.9.3 Release Notes ===================== SciPy 1.9.3 is a bug-fix release with no new features compared to 1.9.2. Authors ====== * Jelle Aalbers (1) * Peter Bell (1) * Jake Bowhay (3) * Matthew Brett (3) * Evgeni Burovski (5) * drpeteb (1) + * Sebastian Ehlert (1) + * GavinZhang (1) + * Ralf Gommers (2) * Matt Haberland (15) * Lakshaya Inani (1) + * Joseph T. Iosue (1) * Nathan Jacobi (1) + * jmkuebler (1) + * Nikita Karetnikov (1) + * Lechnio (1) + * Nicholas McKibben (1) * Andrew Nelson (1) * o-alexandre-felipe (1) + * Tirth Patel (1) * Tyler Reddy (51) * Martin Reinecke (1) * Marie Roald (1) + * Pamphile Roy (2) * Eli Schwartz (1) * serge-sans-paille (1) * ehsan shirvanian (1) + * Mamoru TASAKA (1) + * Samuel Wallan (1) * Warren Weckesser (7) * Gavin Zhang (1) + A total of 31 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. Issues closed for 1.9.3 ------------------------------- * `#3691 <https://github.com/scipy/scipy/issues/3691>`__: scipy.interpolate.UnivariateSpline segfault * `#5286 <https://github.com/scipy/scipy/issues/5286>`__: BUG: multivariate_normal returns a pdf for values outside its... * `#6551 <https://github.com/scipy/scipy/issues/6551>`__: BUG: stats: inconsistency in docs and behavior of gmean and hmean * `#9245 <https://github.com/scipy/scipy/issues/9245>`__: running scipy.interpolate.tests.test_fitpack::test_bisplev_integer_overflow... * `#12471 <https://github.com/scipy/scipy/issues/12471>`__: test_bisplev_integer_overflow: Segmentation fault (core dumped) * `#13321 <https://github.com/scipy/scipy/issues/13321>`__: Bug: setting iprint=0 hides all output from fmin_l_bfgs_b, but... * `#13730 <https://github.com/scipy/scipy/issues/13730>`__: \`scipy.stats.mood\` does not correct for ties * `#14019 <https://github.com/scipy/scipy/issues/14019>`__: ks_2samp throws \`RuntimeWarning: overflow encountered in double_scalars\` * `#14589 <https://github.com/scipy/scipy/issues/14589>`__: \`shgo\` error since scipy 1.8.0.dev0+1529.803e52d * `#14591 <https://github.com/scipy/scipy/issues/14591>`__: Input data validation for RectSphereBivariateSpline * `#15101 <https://github.com/scipy/scipy/issues/15101>`__: BUG: binom.pmf - RuntimeWarning: divide by zero * `#15342 <https://github.com/scipy/scipy/issues/15342>`__: BUG: scipy.optimize.minimize: Powell's method function evaluated... * `#15964 <https://github.com/scipy/scipy/issues/15964>`__: BUG: lombscargle fails if argument is a view * `#16211 <https://github.com/scipy/scipy/issues/16211>`__: BUG: Possible bug when using winsorize on pandas data instead... * `#16459 <https://github.com/scipy/scipy/issues/16459>`__: BUG: stats.ttest_ind returns wrong p-values with permutations * `#16500 <https://github.com/scipy/scipy/issues/16500>`__: odr.Model default meta value fails with __getattr__ * `#16519 <https://github.com/scipy/scipy/issues/16519>`__: BUG: Error in error message for incorrect sample dimension in... * `#16527 <https://github.com/scipy/scipy/issues/16527>`__: BUG: dimension of isuppz in syevr is mistranslated * `#16600 <https://github.com/scipy/scipy/issues/16600>`__: BUG: \`KDTree\`'s optional argument \`eps\` seems to have no... * `#16656 <https://github.com/scipy/scipy/issues/16656>`__: dtype not preserved with operations on sparse arrays * `#16751 <https://github.com/scipy/scipy/issues/16751>`__: BUG: \`stats.fit\` on \`boltzmann\` expects \`bound\` for \`lambda\`,... * `#17012 <https://github.com/scipy/scipy/issues/17012>`__: BUG: Small oversight in sparse.linalg.lsmr? * `#17020 <https://github.com/scipy/scipy/issues/17020>`__: BUG: Build failure due to problems with shebang line in cythoner.py * `#17088 <https://github.com/scipy/scipy/issues/17088>`__: BUG: stats.rayleigh.fit: returns \`loc\` that is inconsistent... * `#17104 <https://github.com/scipy/scipy/issues/17104>`__: BUG? Incorrect branch in \`LAMV\` / \`_specfunc.lamv\` * `#17196 <https://github.com/scipy/scipy/issues/17196>`__: DOC: keepdims in stats.mode is incorrectly documented Pull requests for 1.9.3 ------------------------------ * `#5288 <https://github.com/scipy/scipy/pull/5288>`__: BUG: multivariate_normal returns a pdf for values outside its... * `#13322 <https://github.com/scipy/scipy/pull/13322>`__: Bug: setting iprint=0 hides all output from fmin_l_bfgs_b, but... * `#13349 <https://github.com/scipy/scipy/pull/13349>`__: BUG: stats: Reformulate loggamma._rvs to handle c << 1. * `#13411 <https://github.com/scipy/scipy/pull/13411>`__: BUG: fix out-of-bound evaluations in optimize.minimize, powell... * `#15363 <https://github.com/scipy/scipy/pull/15363>`__: BUG: fix powell evaluated outside limits * `#15381 <https://github.com/scipy/scipy/pull/15381>`__: BUG: fix stats.rv_histogram for non-uniform bins * `#16212 <https://github.com/scipy/scipy/pull/16212>`__: stats.mood: correct for when ties are present * `#16288 <https://github.com/scipy/scipy/pull/16288>`__: BUG: fix a crash in \`fpknot\` * `#16318 <https://github.com/scipy/scipy/pull/16318>`__: MAINT: stats: fix _contains_nan on Pandas Series * `#16460 <https://github.com/scipy/scipy/pull/16460>`__: Fix ttest permutations * `#16506 <https://github.com/scipy/scipy/pull/16506>`__: MAINT: fix SHGO extra arguments * `#16521 <https://github.com/scipy/scipy/pull/16521>`__: BUG: Fix error in error message for incorrect sample dimension... * `#16525 <https://github.com/scipy/scipy/pull/16525>`__: MAINT: stats.ks_2samp: always emit warning when exact method... * `#16528 <https://github.com/scipy/scipy/pull/16528>`__: BUG: fix syevr series segfault by explicitly specifying operator... * `#16562 <https://github.com/scipy/scipy/pull/16562>`__: BUG: optimize: Fix differential_evolution error message. * `#16573 <https://github.com/scipy/scipy/pull/16573>`__: FIX: \`odr.Model\` error with default \`meta\` value * `#16588 <https://github.com/scipy/scipy/pull/16588>`__: FIX: stats: ignore divide-by-zero warnings from Boost binom impl * `#16590 <https://github.com/scipy/scipy/pull/16590>`__: MAINT: stats.vonmises: wrap rvs to -pi, pi interval * `#16630 <https://github.com/scipy/scipy/pull/16630>`__: BUG: eps param no effect fixed * `#16645 <https://github.com/scipy/scipy/pull/16645>`__: MAINT: Ensure Pythran input for lombscargle are contiguous * `#16649 <https://github.com/scipy/scipy/pull/16649>`__: Detect integer overflow in bivariate splines in fitpackmodule.c,... * `#16657 <https://github.com/scipy/scipy/pull/16657>`__: BUG: sparse: Fix indexing sparse matrix with empty index arguments. * `#16669 <https://github.com/scipy/scipy/pull/16669>`__: FIX: spurious divide error with \`gmean\` * `#16701 <https://github.com/scipy/scipy/pull/16701>`__: BUG: fix mutable data types as default arguments in \`ord.{Data,RealData}\` * `#16752 <https://github.com/scipy/scipy/pull/16752>`__: MAINT: stats.boltzmann: correct _shape_info typo * `#16780 <https://github.com/scipy/scipy/pull/16780>`__: BUG: interpolate: sanity check x and y in make_interp_spline(x,... * `#16836 <https://github.com/scipy/scipy/pull/16836>`__: MAINT: avoid \`func_data\`, it conflicts with system header on... * `#16872 <https://github.com/scipy/scipy/pull/16872>`__: BUG: interpolate: work array sizes for RectSphereBivariateSpline * `#16965 <https://github.com/scipy/scipy/pull/16965>`__: BUG: linalg: Fix the XSLOW test test_sgesdd_lwork_bug_workaround() * `#17043 <https://github.com/scipy/scipy/pull/17043>`__: MAINT: fix small LSMR problem * `#17090 <https://github.com/scipy/scipy/pull/17090>`__: MAINT: stats.rayleigh: enforce constraint on location * `#17105 <https://github.com/scipy/scipy/pull/17105>`__: FIX: special: use intended branching for \`lamv\` implementation * `#17166 <https://github.com/scipy/scipy/pull/17166>`__: MAINT: stats.rv_discrete.pmf: should be zero at non-integer argument * `#17176 <https://github.com/scipy/scipy/pull/17176>`__: REL: Prep for SciPy 1.9.3 * `#17190 <https://github.com/scipy/scipy/pull/17190>`__: BUG: special: Fix two XSLOW test failures. * `#17193 <https://github.com/scipy/scipy/pull/17193>`__: MAINT: update meson.build to make it work on IBM i system * `#17200 <https://github.com/scipy/scipy/pull/17200>`__: BLD: fix issue with incomplete threads dependency handling * `#17204 <https://github.com/scipy/scipy/pull/17204>`__: Keepdims incorrectly documneted fix * `#17209 <https://github.com/scipy/scipy/pull/17209>`__: MAINT: Handle numpy's deprecation of accepting out-of-bound integers. * `#17210 <https://github.com/scipy/scipy/pull/17210>`__: BLD: fix invalid shebang for build helper script Checksums ========= MD5 ~~~ 4f24f8e360b9ad4e9e73368d2a45e093 Changelog 7887e0d95aa5a8ffc13c916ffe50b954 README.txt 7cc7a68a35baa1410401cd17c0c1adef scipy-1.9.3-cp310-cp310-macosx_10_9_x86_64.whl befec66a3e966689b06deaab36738d80 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ANN: psutil 5.9.3 released
by Giampaolo Rodola' 18 Oct '22

18 Oct '22

Hello all, I'm glad to announce the release of psutil 5.9.3: https://github.com/giampaolo/psutil About ===== psutil (process and system utilities) is a cross-platform library for retrieving information on running processes and system utilization (CPU, memory, disks, network) in Python. It is useful mainly for system monitoring, profiling and limiting process resources and management of running processes. It implements many functionalities offered by command line tools such as: ps, top, lsof, netstat, ifconfig, who, df, kill, free, nice, ionice, iostat, iotop, uptime, pidof, tty, taskset, pmap. It currently supports Linux, Windows, macOS, Sun Solaris, FreeBSD, OpenBSD, NetBSD and AIX, both 32-bit and 64-bit architectures. Supported Python versions are 2.7 and 3.4+. PyPy is also known to work. What's new ========== 2022-10-18 **Enhancements** - #2040, [macOS]: provide wheels for arm64 architecture. (patch by Matthieu Darbois) **Bug fixes** - #2116, [macOS], [critical]: `psutil.net_connections`_ fails with RuntimeError. - #2135, [macOS]: `Process.environ()`_ may contain garbage data. Fix out-of-bounds read around ``sysctl_procargs``. (patch by Bernhard Urban-Forster) - #2138, [Linux], **[critical]**: can't compile psutil on Android due to undefined ``ethtool_cmd_speed`` symbol. - #2142, [POSIX]: `net_if_stats()`_ 's ``flags`` on Python 2 returned unicode instead of str. (patch by Matthieu Darbois) - #2147, [macOS] Fix disk usage report on macOS 12+. (patch by Matthieu Darbois) - #2150, [Linux] `Process.threads()`_ may raise ``NoSuchProcess``. Fix race condition. (patch by Daniel Li) - #2153, [macOS] Fix race condition in test_posix.TestProcess.test_cmdline. (patch by Matthieu Darbois) Links ===== - Home page: https://github.com/giampaolo/psutil - Download: https://pypi.org/project/psutil/#files - Documentation: http://psutil.readthedocs.io - What's new: https://github.com/giampaolo/psutil/blob/master/HISTORY.rst Hashes ====== psutil-5.9.3-cp27-cp27m-macosx_10_9_x86_64.whl md5: db3e478af16a7887b5e9571d449e8731 sha256: b4a247cd3feaae39bb6085fcebf35b3b8ecd9b022db796d89c8f05067ca28e71 psutil-5.9.3-cp27-cp27m-manylinux2010_i686.whl md5: e961821cf48d049d9349f9729366e698 sha256: 5fa88e3d5d0b480602553d362c4b33a63e0c40bfea7312a7bf78799e01e0810b psutil-5.9.3-cp27-cp27m-manylinux2010_x86_64.whl md5: 61f141ac671a75ef8a57d7ad936dcffc sha256: 767ef4fa33acda16703725c0473a91e1832d296c37c63896c7153ba81698f1ab psutil-5.9.3-cp27-cp27m-win32.whl md5: 07e50d41ab595315d65d485ad9c6ea3e sha256: 9a4af6ed1094f867834f5f07acd1250605a0874169a5fcadbcec864aec2496a6 psutil-5.9.3-cp27-cp27m-win_amd64.whl md5: 0db51fd3eef3b5034676b6c8e49fb771 sha256: 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md5: 35494ef74b945794b1768c0c80eeef72 sha256: 3a7826e68b0cf4ce2c1ee385d64eab7d70e3133171376cac53d7c1790357ec8f psutil-5.9.3-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl md5: ed5ad240fb60f7cdd469058015e4e05f sha256: 9ec296f565191f89c48f33d9544d8d82b0d2af7dd7d2d4e6319f27a818f8d1cc psutil-5.9.3-cp39-cp39-win32.whl md5: c8dbc7322802bc7adc440615bb9b8a8d sha256: 9ec95df684583b5596c82bb380c53a603bb051cf019d5c849c47e117c5064395 psutil-5.9.3-cp39-cp39-win_amd64.whl md5: 213f4bd74b9b9719ec5ea8fd486e589e sha256: 4bd4854f0c83aa84a5a40d3b5d0eb1f3c128f4146371e03baed4589fe4f3c931 psutil-5.9.3.tar.gz md5: 66b847f94545e96b540518ebe19740b4 sha256: 7ccfcdfea4fc4b0a02ca2c31de7fcd186beb9cff8207800e14ab66f79c773af6 -- Giampaolo - https://gmpy.dev/about

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[ANN] Numba 0.56.3
by Valentin Haenel 14 Oct '22

14 Oct '22

Dear all, on behalf of the Numba development community, I am happy to announce the release of Numba 0.56.3. This is a bugfix release to remove the version restriction applied to the setuptools package and to fix a bug in the CUDA target in relation to copying zero length device arrays to zero length host arrays. For more information, please point your browser at: https://numba.discourse.group/t/ann-numba-0-56-3/1600 EOM

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